Assessing Vineyard Resilience to Hydro-Climatic Hazards: An X-band SAR Approach for Agricultural Risk Monitoring

In a context of climate change, agricultural systems are increasingly exposed to natural hazards, ranging from prolonged droughts to extreme precipitation events (IPCC, 2023). Monitoring the resilience of high-value crops, such as vineyards, is therefore critical for effective risk management and adaptation strategies. While remote sensing has been widely employed to investigate vineyard phenology (Giovos et al., 2021), current approaches rely predominantly on optical data and UAV platforms, which are limited by weather conditions and often lack the structural sensitivity required for robust biomass estimation (Weiss et al., 2020).

This study addresses this gap by exploring the potential of Synthetic Aperture Radar (SAR) technology - specifically X-band data from the COSMO-SkyMed constellation - as a tool for assessing vineyard vulnerability and structural response to environmental stressors. A limited but still significant case study is reported in northern Italy, where the winemaking region of Oltrepò pavese is experiencing a drift in crop suitability; a sample of about 40 vineyards with specific azimuth orientations of rows was defined, to avoid possible anisotropy phenomena, then time series of single-pol (HH) CSK data were identified on each vineyard for year 2024. We posit that precise knowledge of vineyard biomass is not only relevant for carbon sink quantification but is also a key indicator of the crop's capability to withstand increasingly warm and dry conditions.

This research analyses the complex interaction between vegetation structure and meteorological hazards, specifically focusing on the influence of accumulated rainfall and dew formation on radar backscatter. Building on previous, multi-sensor SAR observation of vineyards (Bergamaschi et al., 2025) we present an ordinary least squares (OLS) modelling framework to quantify the relationship between hydrometeorological variables and SAR signal variability. Our preliminary results suggest that accumulated recent rainfall acts as a significant predictor of structural changes, with precipitation over the preceding 72 hours explaining over 70% of the local radar signal evolution. This strong correlation underscores the potential of X-band SAR to serve as a reliable proxy for monitoring crop status under hydrological stress. While the proposed OLS model successfully captures the primary drivers of backscatter variability, future developments will aim to enhance risk assessment capabilities through mixed-effects models and the integration of additional biophysical parameters.

This work contributes to making Earth-observation data a valuable resource to natural hazard studies, helping to build a pathway toward operational, all-weather monitoring of agricultural risks in a changing climate.

References

IPCC. (2023). Summary for Policymakers. In Climate Change 2023: Synthesis Report. Contribution of WGs I, II and III to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change. 

Giovos, R., Tassopoulos, D., Kalivas, D., Lougkos, N., & Priovolou, A. (2021). Remote Sensing Vegetation Indices in Viticulture: A Critical Review. Agriculture, 11(5), 457. 

Weiss, M., Jacob, F., & Duveiller, G. (2020). Remote sensing for agricultural applications: A meta-review. Remote Sensing of Environment, 236, 111402.

Bergamaschi, A. Verma, A. Bhattacharya and F. Dell’Acqua (2025). "Joint Analysis of Optical and SAR Vegetation Indices for Vineyard Monitoring: Assessing Biomass Dynamics and Phenological Stages Over Po Valley, Italy", IEEE Access, vol. 13, pp. 153886-153895, 2025.